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Game Theoretic Honeypot Deployment in Smart Grid
The smart grid provides advanced functionalities, including real-time monitoring, dynamic energy management, advanced pricing mechanisms, and self-healing, by enabling the two-way flow of power and data, as well as the use of Internet of Things (IoT) technologies and devices. However, converting the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435919/ https://www.ncbi.nlm.nih.gov/pubmed/32731595 http://dx.doi.org/10.3390/s20154199 |
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author | Diamantoulakis, Panagiotis Dalamagkas, Christos Radoglou-Grammatikis, Panagiotis Sarigiannidis, Panagiotis Karagiannidis, George |
author_facet | Diamantoulakis, Panagiotis Dalamagkas, Christos Radoglou-Grammatikis, Panagiotis Sarigiannidis, Panagiotis Karagiannidis, George |
author_sort | Diamantoulakis, Panagiotis |
collection | PubMed |
description | The smart grid provides advanced functionalities, including real-time monitoring, dynamic energy management, advanced pricing mechanisms, and self-healing, by enabling the two-way flow of power and data, as well as the use of Internet of Things (IoT) technologies and devices. However, converting the traditional power grids to smart grids poses severe security challenges and makes their components and services prone to cyber attacks. To this end, advanced techniques are required to mitigate the impact of the potential attacks. In this paper, we investigate the use of honeypots, which are considered to mimic the common services of the smart grid and are able to detect unauthorized accesses, collect evidence, and help hide the real devices. More specifically, the interaction of an attacker and a defender is considered, who both optimize the number of attacks and the defending system configuration, i.e., the number of real devices and honeypots, respectively, with the aim to maximize their individual payoffs. To solve this problem, game theoretic tools are used, considering an one-shot game and a repeated game with uncertainty about the payoff of the attacker, where the Nash Equilibrium (NE) and the Bayesian NE are derived, respectively. Finally, simulation results are provided, which illustrate the effectiveness of the proposed framework. |
format | Online Article Text |
id | pubmed-7435919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74359192020-08-24 Game Theoretic Honeypot Deployment in Smart Grid Diamantoulakis, Panagiotis Dalamagkas, Christos Radoglou-Grammatikis, Panagiotis Sarigiannidis, Panagiotis Karagiannidis, George Sensors (Basel) Article The smart grid provides advanced functionalities, including real-time monitoring, dynamic energy management, advanced pricing mechanisms, and self-healing, by enabling the two-way flow of power and data, as well as the use of Internet of Things (IoT) technologies and devices. However, converting the traditional power grids to smart grids poses severe security challenges and makes their components and services prone to cyber attacks. To this end, advanced techniques are required to mitigate the impact of the potential attacks. In this paper, we investigate the use of honeypots, which are considered to mimic the common services of the smart grid and are able to detect unauthorized accesses, collect evidence, and help hide the real devices. More specifically, the interaction of an attacker and a defender is considered, who both optimize the number of attacks and the defending system configuration, i.e., the number of real devices and honeypots, respectively, with the aim to maximize their individual payoffs. To solve this problem, game theoretic tools are used, considering an one-shot game and a repeated game with uncertainty about the payoff of the attacker, where the Nash Equilibrium (NE) and the Bayesian NE are derived, respectively. Finally, simulation results are provided, which illustrate the effectiveness of the proposed framework. MDPI 2020-07-28 /pmc/articles/PMC7435919/ /pubmed/32731595 http://dx.doi.org/10.3390/s20154199 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Diamantoulakis, Panagiotis Dalamagkas, Christos Radoglou-Grammatikis, Panagiotis Sarigiannidis, Panagiotis Karagiannidis, George Game Theoretic Honeypot Deployment in Smart Grid |
title | Game Theoretic Honeypot Deployment in Smart Grid |
title_full | Game Theoretic Honeypot Deployment in Smart Grid |
title_fullStr | Game Theoretic Honeypot Deployment in Smart Grid |
title_full_unstemmed | Game Theoretic Honeypot Deployment in Smart Grid |
title_short | Game Theoretic Honeypot Deployment in Smart Grid |
title_sort | game theoretic honeypot deployment in smart grid |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435919/ https://www.ncbi.nlm.nih.gov/pubmed/32731595 http://dx.doi.org/10.3390/s20154199 |
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